ABSTRACT

A sudden fall accident is the main concern for the elderly and disabled people. Automatic detection of the falls from video sequences is an assistive technology for surveillance systems. In this study, a three-stage framework was presented and implemented based on the combination of the data from multiple cameras to address the challenges of occlusion and visibility. In the first stage, the number of used cameras was specified. In the second stage, each camera was decided locally based on its data about the fall incident. In the third and final stage, the aggregation function was used to combine the single camera’s decision considering the coverage rate coefficient of the used cameras. Experiments on the multiple-camera fall dataset demonstrated that our method is comparable to other state-of-the-art methods.

摘要

突发跌倒事故是老年人和残疾人最关心的问题。从视频序列中自动检测跌倒是监控系统的一项辅助技术。在这项研究中，基于来自多个摄像头的数据的组合，提出并实施了一个三阶段框架，以解决遮挡和可见性的挑战。在第一阶段，指定使用的相机数量。在第二阶段，每台摄像机都是根据其坠落事件的数据在当地决定的。在第三阶段和最后阶段，考虑使用相机的覆盖率系数，使用聚合函数组合单个相机的决策。多相机跌倒数据集的实验表明，我们的方法与其他最先进的方法相当。